As for a camera calibration method, various proposals have been made heretofore, one of which is known as a method for computing camera parameters, by placing a featured three-dimensional object, whose configuration has been known in advance, in 3D space, as an index for calibration, and determining how featured points of the three-dimensional object are indicated on a camera image coordinate system.
For instance, in Non-patent document 1, there is disclosed a method for computing camera parameters with 11 degrees of freedom, by means of calibration indices for the featured three-dimensional object. In this respect, proposed is a method for determining calibration camera parameters in the 3D space, by placing the featured three-dimensional object on a position where an image of the featured three-dimensional object can be taken by a camera, and geometrically computing a point, on which the three-dimensional object is indicated in the camera coordinate system. However, according to the method for performing the camera calibration after the camera was installed on the vehicle, as described above, in the case where the object to be calibrated is the camera mounted on the vehicle, the calibration will be performed on vehicle assembling lines in a plant or the like. In a production site, a good workability shall be requisite. In the production site, if the method for performing the calibration by placing the featured three-dimensional object is employed, it is ineffective to place the three-dimensional object as the calibration index, in each calibration. In view of preventing an accident, it is desirable to avoid placing the three-dimensional object to be used for calibration at workers' feet. With respect to the calibration index for performing the camera calibration, it is desirable to select the index that should not cause a problem, even if the workers put their feet on it, such as a pattern painted on a floor in the plant.
In view of the above problem, in Patent document 1, there are proposed a device and a method to be capable of performing the camera calibration according to a simple process, even if the camera calibration is performed in the vehicle production site or the like. And, there is disclosed a method for enabling the camera calibration to be performed in the vehicle assembling lines, with the calibration indices being provided to enable the camera parameters to be set such that they can be displayed at arbitrary points on the image.
Also, in Non-patent document 2, like the method as described in the above Non-patent document 1, there is proposed the method for computing camera parameters in 3D space, by placing the featured three-dimensional object on the position where the image of the featured three-dimensional object can be taken by a camera, and geometrically computing the point, on which the three-dimensional object is indicated on the camera coordinate system.
Furthermore, in the following Non-patent documents 3-5, there are disclosed technical information such as image processing techniques, on which the present invention based, and which will be described later, when explaining the embodiment of the present invention.
Patent document 1:
    Japanese Patent Laid-open Publication No. 2001-245326    Non-patent document 1:    Pages 1-21 of “Camera calibration without Feature Extraction” written by Luc Robert, published by Institute National de Recherche en Informatique Automatique, Research Report No. 2204, issued in February 1994Non-patent document 2:    Pages 364-374 of “An Efficient and Accurate Camera Calibration Technique for 3D Machine Vision” written by Roger Y. Tsai, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Miami Beach, Fla., issued inNon-patent document 3:    Pages 11-41 of “Computer vision” written by Jun Satoh, first issue, third print, published by Corona-Sha, on October 10, 2001Non-patent document 4:    “Geometric Framework for Vision I: Single View and Two-View Geometry” written by Andrew Zisserman, issued by Robotics Research Group, University of Oxford, on Apr. 16, 1997, <URL:http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/EPSRC_SSAZ/epsrc_ssaz.html> retrieved on Sep. 3, 2004Non-patent document 5:    Pages 11-16 of “Multiple View Geometry in Computer Vision” written by Richard Hartley and Andrew Zisserman, published by Cambridge University Press., in August, 2000